The invention relates to a method for operating a motor vehicle, wherein in order to determine a total strategy, required basic data predictively describing the operation of the motor vehicle is determined for a route known in advance from input data comprising route data, the operating strategy of the motor vehicle is evaluated for determination of the total strategy based on the basic data and the vehicle is operated according to the total operating strategy.
With modern motor vehicles, situations occur when it is already known which route the motor vehicle will be traveling on during the consequent operation. Similar route data can originate for example from a navigation system of the motor vehicle, which determines a course of travel starting from a current position of the motor vehicle up to a destination location. This kind of accurate information about future routes to be traveled on with the vehicle can be used in order to plan in advance a total operating strategy to be applied to at least one component of the motor vehicle, which can be composed of partial strategies applied to different components of the route and optimized based on a certain criterion and then carried out while driving on a route that is known in advance.
An example of such planning in advance of an total operating strategy is a strategy for hybrid vehicles, in particular for so-called plug-in hybrids. These vehicles are provided with a fuel reservoir that is used as an energy storage device, and with a battery, with which can be powered by an internal combustion engine and an electromotor of the vehicle. A total operating strategy for such a hybrid motor vehicle can comprise a number of different partial strategies, which may include an operating mode or several operating modes, as well conditions for their concrete application. For example, an operating mode can be provided in which the motor vehicle can be operated purely electrically, another operating in which the motor vehicle is operated without charging the battery, and a third operating mode in which the motor vehicle is operated with a targeted charging of the battery by the internal combustion motor, and a fourth operating mode in which the electromotor is operatively supported by the internal combustion engine. Partial operating strategies and/or the total operating strategy can contain priorities for individual operating mode and for example aim at maintaining constant the activation criteria for the activation of individual operating modes and for example aim at increasing the charging status of the battery powering one of the electromotors constant or at increasing it to a certain extent, or to use the electromotor as much as possible and the like. In order to determine a total operating strategy, it can be therefore specified when and which partial strategies should be used during the course of the route that is known in advance, or portions of the route can be directly assigned to an operation mode. The goal of optimization of such a total strategy can be for example that the battery should be emptied with the lowest possible consumption of fuel upon arrival to the destination, where it can be charged again. It goes without saying that combinations of several/other optimization goals are also conceivable.
The operating strategy of a plug-in hybrid vehicle can thus also for example influence how fast the energy from the battery is used up during the traveling, in particular depending on the priorities, for example by changing the switch-on and switch-off limits. As a rule, the goal is to use up electric energy completely until the motor vehicle arrives again to a charging facility. At the same time, however, the electric energy should be used when the electromotor is operated with the best possible efficiency and the internal combustion engine provides a relatively poor efficiency. The result of the latter can be that it may be also useful to charge the battery during a segment of the route from the internal combustion engine in order to be able to continue driving later with electric energy.
Various approaches to the use of predictive route data can be used in order to determine an operating strategy so as to achieve such optimization goals.
So for example, DE 198 31 487 C1 proposes a method for operating a battery of a hybrid drive of a motor vehicle, wherein information regarding a route to be completed is recorded and a calculation of the expected power requirements for the hybrid drive is carried out during the course of the travel route while taking into account the recorded information. The driving route is divided on the basis of the route data in order to determine an average power requirement for the components of the route so that dynamic processes are averaged. The strategy is then determine dwith a comparison of efficiency.
EP 2 620 343 A2 relates to a method for operating a hybrid drive unit for a motor vehicle, wherein the route data about a planned route to be covered is also received and a total expected power for the planned route is determined, wherein an operating strategy is then implemented for the planned route in dependence on the required total power that is expected, namely in such a way that after the completion of the route, the charging state of the battery will reach a predetermined value.
According to other known approaches, the profiles of expected power and speed are calculated from the route data and the total strategy is then optimized directly based on this.
However, there are several problems with these known method. So for example, essential information is lost during the calculation of the average values, in particular information about the distribution of the power, which leads to an inferior prediction and therefore results in a flawed total operating strategy. The calculation of the performance process per se is not very computationally intensive, but the optimization of the total operating strategy from such a performance process over the entire route definitely is. In addition, it is not possible to predict the speed profile with precision even if the general conditions are well understood, which means that a complicated optimization can produce a false result, or in an extreme case even lead to completely false results.